Within the field of computing, many scenarios involve documents comprising an aggregation of a variety of content, such as typed text, handwritten text and drawings, mathematical equations, embedded images, videos, and other forms of media and data. The text may comprise a variety of formatting, such as a paragraph structure; tabular data that is formatted as a set of rows and columns; and margins and indenting. Formatting may also be applied to position sets of content relative to one another; e.g., an inline layout may be applied that causes some content (such as text) to provide space that accommodates other content (such as an image).
Within such scenarios, recognition techniques may be applied to identify the contents of a portion of the document, and to translate particular forms of content into other content with a greater degree of structure. As a first such example, a handwriting recognition technique may accept an image of a handwritten text, and/or may monitor live input from a touch device such as a stylus, and may translate the strokes of the image and/or input into a recognized set of alphanumeric symbols, which may then be encoded in a standardized format such as ASCII or Unicode. As a second such example, alphanumeric characters in a document (including alphanumeric characters encoded in a standardized format) may be semantically evaluated to identify the semantic content of an expression, which may enable a translation of the expression into a different language. Many such techniques may be utilized to recognize the contents of the document and to take appropriate responsive actions.